aymericbeaumet

Ever wanted to delete all your likes/favorites from Twitter but only found broken/expensive tools? You are in the right place.

1. Go to: https://twitter.com/{username}/likes
2. Open the console and run the following JavaScript code:

setInterval(() => {
  for (const d of document.querySelectorAll('div[data-testid="unlike"]')) {
    d.click()
 }

mndrake

# originally from: http://stackoverflow.com/questions/42528400/plot-brushing-or-accessing-drawn-shape-geometry-for-spatial-subsets-in-shiny-lea
# uses https://github.com/bhaskarvk/leaflet.extras

library(shiny)
library(leaflet)
library(leaflet.extras)
library(sp)

cities <- structure(list(AccentCity = c("Saint Petersburg", "Harare", "Qingdao", 
                                        "Addis Abeba", "Xian", "Anshan", "Rongcheng", "Kinshasa", "New York", 

ramhiser

# The data set and model are described in the *brms* vignette
library(brms)

url <- paste0("https://raw.githubusercontent.com/mages/diesunddas/master/Data/ClarkTriangle.csv")
loss <- read.csv(url)

set.seed(42)

# Generated a random continuous feature
loss$ramey <- runif(nrow(loss))

wch

library(shiny)

# Example usage:
# lmGadget(mtcars, "wt", "mpg")
#
# Returns a list with two items:
#   $data: Data with excluded rows removed.
#   $model: lm (model) object.
lmGadget <- function(data, xvar, yvar) {
  library(miniUI)

mbostock

license: gpl-3.0

hadley

ks.default <- function(rows) seq(2, max(3, rows %/% 4))

many_kmeans <- function(x, ks = ks.default(nrow(x)), ...) {
  ldply(seq_along(ks), function(i) {
    cl <- kmeans(x, centers = ks[i], ...)
    data.frame(obs = seq_len(nrow(x)), i = i, k = ks[i], cluster = cl$cluster)
  })
}

all_hclust <- function(x, ks = ks.default(nrow(x)), point.dist = "euclidean", cluster.dist = "ward") {